Principal Data Analyst

Position Responsibilities may include, but not limited to

• Lead high‑impact analytics initiatives from problem framing through delivery; quantify value, design robust analyses, and communicate recommendations to business partners and executives
• Partner with business leaders to identify analytics opportunities and deliver actionable insights. Present findings and recommendations to partners and executive leadership in clear, compelling formats
• Develop analytics products and solutions using Databricks, modern Business and Artificial Intelligence tools and Agile principles
• Implement advanced analytics where applicable, leveraging Python for advanced analytics, automation, and integration with Databricks workflows
• Architect and publish trusted Power BI datasets and dashboards (DAX, Power Query, semantic models), establishing standards for usability and adoption
• Build performant Databricks workflows (notebooks, jobs, SQL Warehouses) to wrangle large datasets, engineer features, and automate recurring analyses
• Develop Python scripts for automation, data wrangling, and integration with Databricks and Azure services
• Partner with Data Engineering on Azure data stack components (Data Factory, ADLS, Synapse/Fabric pipelines) for scalable data solutions
• Own analysis quality: data validation, experiment/study design, sensitivity checks, and reproducibility (versioning, documentation)
• Define and monitor KPIs; create executive scorecards and operational reporting that tie directly to business objectives
• Coach/mentor analysts and BI developers; uplift storytelling, statistical thinking, and visualization craftsmanship across the team
• Collaborate with Data Governance and Compliance to ensure appropriate use of PHI and adherence to privacy/security controls
• Facilitate data stewardship and literacy across the business
• Drive adoption of data products to scale data value
• Stay current with emerging technologies and recommend enhancements to the analytics stack

Required Skills and Experience

• Bachelor’s degree in Data Science, Computer Science, Statistics, Economics or related field
• 8–10+ years in analytics roles, including 3+ years leading projects
• Proven impact delivering analytics in complex environments (multi‑source data, ambiguous scope) with measurable business outcomes
• Experience operating in healthcare data environments (or demonstrated ability to quickly adapt to such contexts)
• Demonstrated ability to mentor junior analytics professionals
• Statistical and financial analytics expertise with deep understanding of appropriate study design and analysis techniques and business case development
• Azure Data Stack: Data Factory, ADLS, Synapse/Fabric pipelines; familiarity with security and governance features
• Databricks: Spark/SQL, notebooks & jobs, performance tuning, SQL Warehouses
• SQL: Strong proficiency (ANSI/T‑SQL); query optimization over large, partitioned tables
• R: Applied analytics using tidyverse/ggplot2; reproducible workflows; statistical testing and modeling fundamentals
• Python: Data wrangling, automation, integration with Databricks and Azure services
• Fabric and Power BI: Data modeling, DAX, Power Query (M), calculation groups, row‑level security, deployment pipelines
• Versioning & Reproducibility: Git‑based workflows; disciplined documentation and peer review
• Executive storytelling: distill and translate complex analyses into clear narratives and recommended actions or analytics solutions
• Stakeholder partnership: influence cross‑functional partners; set expectations and drive alignment
• Demonstrated ability to deliver projects with undefined, large and/or complex scope
• Agile delivery
• Mentorship: develop analysts’ craft (methodology, viz/design, communication)
• Product mindset: define problem statements, success metrics, and iterate with feedback – drives adoption of analytics products and solutions
• Ownership & judgment: operate independently, make sound trade‑offs, and uphold high quality standards

Preferred Skills and Experience

• Master’s degree in Economics, Statistics, Data Science, Computer Science or related field
• Certifications in Databricks, Power BI, or cloud platforms (Azure preferred)
• Experience with machine learning frameworks and MLOps practices
• Familiarity with data governance tools and compliance standards
• Knowledge of advanced BI features (Power BI Copilot, AI-driven analytics)
• Familiarity with healthcare risk adjustment models such as HCC and CDPS
• Familiarity with claims groupers such as Milliman’s HCG
• Product management training or analytics product delivery experience

Physical Requirements

• Repetitive motions that include the wrists, hands and/or fingers
• Sedentary work that primarily involves sitting, remaining in a stationary position for prolonged periods
• Visual perception to perform job including peripheral vision, depth perception, and the ability to adjust focus

Originally posted on Himalayas